# To Install a Packageinstall.packages("tidyverse")# To Load a Packagelibrary(tidyverse)
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You only have to install a package once (one exception)
You must load a library every time you open an R file (.R, .qmd, .rmd, etc) or restart R/RStudio
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Important
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Important
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A new install of R will remove all installed packages. You must either re-install the packages or save them prior to a new R installation. I’ll cover how to save them at a later date
# For CSVdata <-read.csv("file_name.csv")# For TSVdata <-read_tsv("file_name.tsv")# For SAVlibrary(haven)data <-read_sav("file_name.sav")# For EXCELlibrary(readxl)data <-read_xlsx("file_name.xlsx")data <-read_xls("file_name.xls")
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Variable Types
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Variable Types
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Numerical
A positive or negative number between (- \(\infty\), \(\infty\))
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Integer
A positive or negative whole number between (- \(\infty\), \(\infty\))
Factor
A grouping category
Character
A text string
Logical
A TRUE or FALSE value (e.g., Is X > 1?)
Date
Exactly what you think it is
{dplyr} R package
Uses for the dplyr package
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Integer
A positive or negative whole number between (- \(\infty\), \(\infty\))
Factor
A grouping category
Character
A text string
Logical
A TRUE or FALSE value (e.g., Is X > 1?)
Date
Exactly what you think it is
{dplyr} R package
Uses for the dplyr package
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Primary use is to transform and manipulate data in a data set
Anyone here who has maybe used database data will see it mimics SQL programming
Note
For anyone who might work with database data, you can pull data from external databases with R and RStudio. We won’t cover that in this workshop but you can do it
Live-ish Coding
Open the data_clean.qmd file provided. We’re going to walk through some example code and then live code a little bit
{stringr} R package
Uses for the stringr package
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Anyone here who has maybe used database data will see it mimics SQL programming
Note
For anyone who might work with database data, you can pull data from external databases with R and RStudio. We won’t cover that in this workshop but you can do it
Live-ish Coding
Open the data_clean.qmd file provided. We’re going to walk through some example code and then live code a little bit
{stringr} R package
Uses for the stringr package
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Primarily used for dealing with character or string data
Useful for free response questions
Essentially it’s the dplyr package for string variable types
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Live-ish Coding
Go back to the data_clean.qmd file provided. We’re going to walk through some example code and then live code a little bit
{lubridate} R package
Uses for the lubridate package
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Live-ish Coding
Go back to the data_clean.qmd file provided. We’re going to walk through some example code and then live code a little bit
{lubridate} R package
Uses for the lubridate package
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Primarily used for dealing with dates
Provides handy function for converting date formats into other date formats
E.g., (MM-DD-YY to DD-MM-YY or Month Date, Year)
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Tip
It won’t auto convert your dates to weird incorrect formats like certain spreadsheet programs might.
Live-ish Coding
Go back to the data_clean.qmd file provided. We’re going to walk through some example code and then live code a little bit
{ggplot2} R package
Uses for the ggplot2 package
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Tip
It won’t auto convert your dates to weird incorrect formats like certain spreadsheet programs might.
Live-ish Coding
Go back to the data_clean.qmd file provided. We’re going to walk through some example code and then live code a little bit
{ggplot2} R package
Uses for the ggplot2 package
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This may be the most popular package download in R and it’s probably not close
This is THE visualization package in R. If you can THINK of a graphic, this package can create it
E.g. box plots, box and whisker plots, violin plots, bar graphs, etc
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If you’re REALLY good, you can do this (credit @ralitza_s)
“Live”ish Coding
Go back to the data_clean.qmd file provided. We’re going to walk through some example code and then live code a little bit
library(haven)# For SPSSwrite_sav(df, path ="filename.sav")# For SASwrite_sas(df, path ="filename.sas")
write.csv(df, file ="filename.csv")
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Lunch Break
Back at 2pm
Putting It All Together From Start To Finish
Statistical Analyses in R
Correlation
Assumptions (Fields et al, 2012)
On at least an interval scale
Normality of Residuals
Live-ish Coding
Please see correlation.qmd file provided
T Tests
Assumptions (Fields et al, 2012)
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Lunch Break
Back at 2pm
Putting It All Together From Start To Finish
Statistical Analyses in R
Correlation
Assumptions (Fields et al, 2012)
On at least an interval scale
Normality of Residuals
Live-ish Coding
Please see correlation.qmd file provided
T Tests
Assumptions (Fields et al, 2012)
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Normality of Residuals
Independent Observations
Homogeneity of Variance
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Live-ish Coding
Please see the ttest.qmd file provided
Regression
Assumptions (Fields et al, 2012)
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Live-ish Coding
Please see the ttest.qmd file provided
Regression
Assumptions (Fields et al, 2012)
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Outliers and Influential Cases
Normality of Residuals
Independent Observations
Homogeneity of Variance
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Important
While important, outliers and influential cases rarely influence results with a sufficient sample size. Also difficult to say what “is” and “isn’t” an outlier. Outlier shouldn’t always mean removal
Live-ish Coding
Please open the regression.qmd file provided
End of Day 1
Downloading Material For Day 2
You can download all the materials for Day 2 of this workshop here * You want the anova.qmd, nonparametric.qmd, intro_qarto.qmd, mlm.qmd, sem.qmd and factor_analysis.qmd
ANOVA: Including Repeated Measures & Factorial
Assumptions (Fields et al, 2012)
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Important
While important, outliers and influential cases rarely influence results with a sufficient sample size. Also difficult to say what “is” and “isn’t” an outlier. Outlier shouldn’t always mean removal
Live-ish Coding
Please open the regression.qmd file provided
End of Day 1
Downloading Material For Day 2
You can download all the materials for Day 2 of this workshop here * You want the anova.qmd, nonparametric.qmd, intro_qarto.qmd, mlm.qmd, sem.qmd and factor_analysis.qmd
ANOVA: Including Repeated Measures & Factorial
Assumptions (Fields et al, 2012)
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Normality Within Groups
Homogeneity of Variance
Independent Observations
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Live-ish Coding
Please open the anova.qmd file provided
Non-Parametric Tests
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Live-ish Coding
Please open the anova.qmd file provided
Non-Parametric Tests
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Wilcoxon Ranked-Sum Test (i.e., Mann–Whitney Test)
Non-parametric equivalent of the independent samples t-test
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Wilcoxon Signed-Rank Test
Non-parametric equivalent of the dependent sample t-test
Kruskal–Wallis Test
Non-parametric equivalent of an ANOVA
Friedman’s Test
Non-parametric equivalent of a repeated measures ANOVA
Live-ish Coding
Please open the nonparametric.qmd file
EFA & CFA
EFA Assumptions (Fields et al, 2012)
Sufficient Sample Size
Normality of Items
Correlation Between Items1
Appropriate Determinant (Det \(>\) 1 x 10-5)
Important
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Wilcoxon Signed-Rank Test
Non-parametric equivalent of the dependent sample t-test
Kruskal–Wallis Test
Non-parametric equivalent of an ANOVA
Friedman’s Test
Non-parametric equivalent of a repeated measures ANOVA
Live-ish Coding
Please open the nonparametric.qmd file
EFA & CFA
EFA Assumptions (Fields et al, 2012)
Sufficient Sample Size
Normality of Items
Correlation Between Items1
Appropriate Determinant (Det \(>\) 1 x 10-5)
Important
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We want variables to correlate however we do not want them to correlate either too low (r\(<\) .30) or too high (r\(>\) .80) across multiple items
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CFA Assumptions
Multivariate Normality
Live-ish Coding
Please open the factor_analysis.qmd file
Lunch Break
Back at 2pm
SEM
Assumptions To Test (Kaplan, 2001, p. 15218)
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CFA Assumptions
Multivariate Normality
Live-ish Coding
Please open the factor_analysis.qmd file
Lunch Break
Back at 2pm
SEM
Assumptions To Test (Kaplan, 2001, p. 15218)
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Multivariate Normality
No Systematic Missing Data
Sufficiently Large Sample Size
Correct Model Specification
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Live-ish Coding
Please open the sem.qmd file
MLM (Fields et al, 2012)
Assumptions To Test
Outliers and Influential Cases
Normality of Residuals
Independent Observations1
Homogeneity of Variance
A Note On Independence
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Live-ish Coding
Please open the sem.qmd file
MLM (Fields et al, 2012)
Assumptions To Test
Outliers and Influential Cases
Normality of Residuals
Independent Observations1
Homogeneity of Variance
A Note On Independence
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This assumption is not necessarily a concern given that MLM assumes observations are nested (Fields et al, 2012)
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Live-ish Coding
Please open the mlm.qmd file
Quarto: Code + Text
The Holy Grail of Reproducibility
What if I told you that it was possible to generate 95% of what you need for a manuscript within RStudio AND you could integrate your analyses as well?
What if I also said you could export this to Microsoft Word?
Let’s Talk About Quarto
Please open the intro_quarto.qmd file
Final Thoughts
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Live-ish Coding
Please open the mlm.qmd file
Quarto: Code + Text
The Holy Grail of Reproducibility
What if I told you that it was possible to generate 95% of what you need for a manuscript within RStudio AND you could integrate your analyses as well?
What if I also said you could export this to Microsoft Word?
Let’s Talk About Quarto
Please open the intro_quarto.qmd file
Final Thoughts
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Firstly, thank you for your time this weekend and I hope you’ve learned something
Second, this is A LOT. I crammed stuffed about 2 years of statistical analyses time and practice into like 2 days. It’s okay and normal if you’re swimming. I’m here if anyone has any questions after or even if they’re using R and trying to do an actual analysis in R. People ask me for help all the time. I’m happy to help
Finally, one last “minor” detail. Some of you already know this but lets just check out the following link
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=======
};
// fire slideEnter for tabby tab activations (for htmlwidget resize behavior)
document.addEventListener("tabby", fireSlideEnter, false);
deck.on("slidechanged", function (event) {
fireSlideChanged(event.previousSlide, event.currentSlide);
});
}
function workaroundMermaidDistance(deck) {
if (window.document.querySelector("pre.mermaid-js")) {
const slideCount = deck.getTotalSlides();
deck.configure({
mobileViewDistance: slideCount,
viewDistance: slideCount,
});
}
}
function handleWhiteSpaceInColumns(deck) {
for (const outerDiv of window.document.querySelectorAll("div.columns")) {
// remove all whitespace text nodes
// whitespace nodes cause the columns to be misaligned
// since they have inline-block layout
//
// Quarto emits no whitespace nodes, but third-party tooling
// has bugs that can cause whitespace nodes to be emitted.
// See https://github.com/quarto-dev/quarto-cli/issues/8382
for (const node of outerDiv.childNodes) {
if (node.nodeType === 3 && node.nodeValue.trim() === "") {
outerDiv.removeChild(node);
}
}
}
}
return {
id: "quarto-support",
init: function (deck) {
controlsAuto(deck);
previewLinksAuto(deck);
fixupForPrint(deck);
applyGlobalStyles(deck);
addLogoImage(deck);
tweakSlideNumber(deck);
addFooter(deck);
addChalkboardButtons(deck);
handleTabbyClicks();
handleSlideChanges(deck);
workaroundMermaidDistance(deck);
handleWhiteSpaceInColumns(deck);
},
};
};
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